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アカデ1201 確率論的機械学習「海外手配」
開催期間:2022/12/01~2023/03/31

Probabilistic Machine Learning(Adaptive Computation and Machine Learning series) hardcover 944 p. 22

Probabilistic Machine Learning(Adaptive Computation and Machine Learning series) hardcover 944 p. 22

著者:Murphy, Kevin P.


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  • 現地価格:$110.00
  • 組合員価格:¥16,698 (税込)

内容の説明

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author's 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.

登録情報

商品コード:1033377432
出版社: The MIT Press
出版年月: 2022/03
ISBN-10: 0262046822
ISBN-13: 978-0-262-04682-4
出版国: アメリカ合衆国
装丁: hardcover/Geb./rel.
媒体: 冊子
ページ数: 944 p.
ジャンル: 人工知能



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